Financial Modeling Using Sampling-Importance Resampling

While Bayesian methodology has been for decades widely applied to econometric models, robust methods had just lately gained more attention of econometricians. More recently, simulation-based techniques, such as the Sampling-Importance Resampling (SIR) algorithm, have become useful and popular approaches to statistical problems. This article puts together the robust and Bayesian approaches through the SIR technique. Using financial models we show how the statistics usually obtained through the SIR technique can be enhanced by the incorporation of robust aspects. For these models we investigate the posterior inference sensitivity in relation to the change in the likelihood and prior distribution, and obtain the SIR point estimates as well as confidence intervals, which are compared to classical and robust solutions.